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https://api-inference.huggingface.co/models/Hate-speech-CNERG/dehatebert-mono-arabic
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Hate-speech-CNERG/dehatebert-mono-arabic Hate-speech-CNERG/dehatebert-mono-arabic
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pytorch

tf

Contributed by

Hate-ALERT university
4 team members · 9 models

How to use this model directly from the 🤗/transformers library:

			
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from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hate-speech-CNERG/dehatebert-mono-arabic") model = AutoModelForSequenceClassification.from_pretrained("Hate-speech-CNERG/dehatebert-mono-arabic")

This model is used detecting hatespeech in Arabic language. The mono in the name refers to the monolingual setting, where the model is trained using only Arabic language data. It is finetuned on multilingual bert model. The model is trained with different learning rates and the best validation score achieved is 0.877609 for a learning rate of 2e-5. Training code can be found at this url

For more details about our paper

Sai Saketh Aluru, Binny Mathew, Punyajoy Saha and Animesh Mukherjee. "Deep Learning Models for Multilingual Hate Speech Detection". Accepted at ECML-PKDD 2020.

Please cite our paper in any published work that uses any of these resources.

@article{aluru2020deep,
  title={Deep Learning Models for Multilingual Hate Speech Detection},
  author={Aluru, Sai Saket and Mathew, Binny and Saha, Punyajoy and Mukherjee, Animesh},
  journal={arXiv preprint arXiv:2004.06465},
  year={2020}
}